{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          R         F         M  类别数目\n",
      "0 -0.138183  1.050189  0.397381   343\n",
      "1 -0.172012 -0.683968 -0.305443   517\n",
      "2  3.405640 -0.295148  0.487604    40\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "data = pd.read_excel(r'i_nuc.xls',index_col= 'Id',sheet_name='Sheet2')\n",
    "outputfile = r'data1.xls'\n",
    "k = 3 # 聚类的类别\n",
    "iteration = 500 # 聚类的最大循环次数\n",
    "\n",
    "zscoredfile = r'zscoreddata.xls'\n",
    "\n",
    "data_zs = 1.0 * (data-data.mean())/data.std() # 数据标准化\n",
    "data_zs.to_excel(zscoredfile,index = False) # 数据写入\n",
    "\n",
    "from sklearn.cluster import KMeans \n",
    "model = KMeans(n_clusters=k,n_jobs=4,max_iter=iteration) # 分为k类，并发数4\n",
    "\n",
    "model.fit(data_zs) # 开始聚类\n",
    "\n",
    "r1 = pd.Series(model.labels_).value_counts() # 统计各个类别的数目\n",
    "r2 = pd.DataFrame(model.cluster_centers_) # 找出聚类中心\n",
    "r = pd.concat([r2,r1],axis=1) # 横向连接（0是纵向），得到聚类中心对应类别下的数目\n",
    "\n",
    "r.columns = list(data.columns) + [u'类别数目'] # 重命名表头\n",
    "print(r) # 输出原始数据及其类别\n",
    "\n",
    "r = pd.concat([data,pd.Series(model.labels_,index = data.index)],axis=1) # 详细输出每个样本对应的类别\n",
    "r.columns = list(data.columns)+[u'聚类类别'] # 重命名表头\n",
    "r.to_excel(outputfile) # 保存结果\n",
    "\n",
    "def density_plot(data):\n",
    "    import matplotlib.pyplot as plt\n",
    "    plt.rcParams['font.sans-serif']=['SimHei'] # 用来正确显示中文标签\n",
    "    plt.rcParams['axes.unicode_minus'] = False # 用来正确显示负号\n",
    "    p = data.plot(kind='kde',linewidth=2,subplots=True,sharex=False)\n",
    "    [p[i].set_ylabel(u'density') for i in range(k)]\n",
    "    plt.xlabel('group%s'%(i+1))\n",
    "    plt.legend()\n",
    "    return plt\n",
    "\n",
    "pic_output = r'pd_' # 输出概率密度图\n",
    "for i in range(k):\n",
    "    density_plot(data[r['聚类类别']==i]).savefig(u'%s%s.png' % (pic_output, i))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'sklearn' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-8-607dda0082db>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m sklearn.cluster.KMeans(n_clusters=8,\n\u001b[0m\u001b[1;32m      2\u001b[0m                       \u001b[0minit\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'k-means++'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m                       \u001b[0mn_init\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m                       \u001b[0mmax_iter\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m300\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m                       \u001b[0mtol\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0.0001\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'sklearn' is not defined"
     ]
    }
   ],
   "source": [
    "sklearn.cluster.KMeans(n_clusters=8,\n",
    "                      init='k-means++',\n",
    "                      n_init=10,\n",
    "                      max_iter=300,\n",
    "                      tol=0.0001,\n",
    "                      precompute_distances='auto',\n",
    "                      verbose=0,\n",
    "                      random_state=None,\n",
    "                      copy_x=True,\n",
    "                      n_jobs=1,\n",
    "                      algorithm='auto')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
